Simulation of Temporal Correlation Detection using HfO2-Based ReRAM Arrays

Sarah Rafiq, K. Beckmann, N. Cady
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Abstract

As CMOS scaling approaches its limitation, the power consumption of computations performed using the von Neumann architecture have become an issue. As a promising alternative solution, Resistive Random Access Memory (ReRAM) overcomes this bottleneck by enabling computationin-memory. In this work, arrays of HfO2-based bipolar ReRAM are simulated to carry out one such computation, called temporal correlation detection in binary processes. The correlation detection algorithm is presented, and the ReRAM model of fabricated devices was used in a Python-based simulation. The correlated and uncorrelated processes were assigned to ReRAM devices in a 5x5 array, where the ReRAM with correlated process was driven to a high conductance over time. The results show that the correlated processes are successfully detected over time.
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基于hfo2的ReRAM阵列时间相关检测仿真
随着CMOS缩放接近其极限,使用冯·诺伊曼架构进行计算的功耗已成为一个问题。作为一种有前途的替代解决方案,电阻随机存取存储器(ReRAM)通过实现内存计算克服了这一瓶颈。在这项工作中,模拟了基于hfo2的双极ReRAM阵列来执行这样的计算,称为二进制过程中的时间相关检测。提出了相关检测算法,并利用制备器件的ReRAM模型进行了基于python的仿真。将相关和不相关的过程分配给5x5阵列的ReRAM器件,其中具有相关过程的ReRAM随着时间的推移被驱动到高电导。结果表明,随着时间的推移,相关过程被成功地检测到。
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